ABSTRACT Alzheimer?s disease (AD) is the most common form of dementia in the elderly population. While several peptide and protein biomarkers in cerebrospinal fluid (CSF) have been used for AD diagnosis, an unequivocal diagnosis in the early phases of AD is still lacking. Perhaps more importantly, the discovery and establishment of reliable biomarkers capable of monitoring progression and degree of cognitive impairment as well as potential efficacy of therapy remains a major challenge. Furthermore, the correlation between CSF protein/peptide biomarkers and changes in the brain structure/function and cognition is not well established. In order to address these challenges and fill in existing knowledge gaps, we propose to employ a multi-faceted approach combining a suite of mass spectrometry-based technologies enabled by innovative multiplexed tagging strategies, bioinformatics tools and clinically-available measures to discover, identify and evaluate potential biomarkers of AD in CSF obtained from asymptomatic cognitively-healthy middle-aged adults, older cognitively-normal adults, and patients with mild cognitive impairment (MCI) and AD. We propose the following specific aims: Specific Aim 1 ? To conduct in-depth analysis of site-specific glycoproteome and endogenous glycopeptidome in CSF from subjects in control, preclinical, MCI, AD groups, respectively. Specific Aim 2 ? To discover and identify a panel of candidate glycoprotein/glycopeptide biomarkers at different stages of AD using multiplexed dimethylated leucine (DiLeu) reagents-enabled quantitative glycoproteomics approach along with machine learning classification algorithms for improved diagnosis of AD. Specific Aim 3 ? To validate the CSF AD biomarkers, in plasma samples collected from individuals with MCI and dementia, using targeted quantitative proteomics approaches and ELISA assay along with association with AD-related clinical, cognitive and neuroimaging measures. This project uniquely integrates advances in MS-based multiplexed quantitative glycoproteomics and bioinformatics tools with neuroimaging and clinical measures to enable more comprehensive discovery and validation of CSF biomarkers in AD. The proposed research will be performed in collaboration with a multi-disciplinary team of investigators including Drs. Cynthia Carlsson, Henrik Zetterberg, Ozioma Okonkwo and David Page. This multifaceted approach will enable identification of biomarkers of AD in CSF that offer improved sensitivity and specificity for diagnosis and predict dementia onset and progression. These biomarkers would be invaluable in designing therapeutics for patient care and more efficient clinical trials of disease modifying therapies. The advances in technology and new insights will have broad impact on translational medicine.